Hybrid active and passive people metering for audience measurement

ABSTRACT

Hybrid active and passive people metering for audience measurement is disclosed. An example method disclosed herein to perform people metering for audience measurement comprises obtaining an image sequence depicting a scene in which an audience is expected to be present, comparing an image sequence signature representative of the image sequence with a set of reference signatures to determine a comparison result, and controlling audience prompting performed by a people meter based on the comparison result.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement and, moreparticularly, to hybrid active and passive people metering for audiencemeasurement.

BACKGROUND

Audience measurement systems typically include one or more device metersto monitor the media presented by one or more media presentation deviceslocated at a monitored site. Many such audience measurement systems alsoinclude one or more people meters to obtain information characterizingthe composition(s) of the audience(s) in the vicinity of the mediapresentation device(s) being monitored. Prior people meters generallyfall into two categories, namely, active people meters or passive peoplemeters. An active people meter obtains audience information by activelyprompting an audience member to press an input key or otherwise enterinformation via the people meter. A passive people meter obtainsaudience information by passively monitoring the audience, usually byusing facial recognition techniques to identify the individual audiencemembers included in the audience.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example audience measurement systememploying hybrid people metering as disclosed herein.

FIG. 2 is a block diagram of an example hybrid people meter that can beused to implement the example audience measurement system of FIG. 1.

FIG. 3 is a block diagram illustrating an example implementation of thehybrid people meter of FIG. 2.

FIG. 4 is a flowchart representative of first example machine readableinstructions that may be executed to implement the example hybrid peoplemeters of FIGS. 2 and/or 3 for use in the example audience measurementsystem of FIG. 1.

FIG. 5 is a flowchart representative of second example machine readableinstructions that may be executed to implement the example hybrid peoplemeters of FIGS. 2 and/or 3 for use in the example audience measurementsystem of FIG. 1

FIG. 6 is a flowchart representative of third example machine readableinstructions that may be executed to implement the example hybrid peoplemeters of FIGS. 2 and/or 3 for use in the example audience measurementsystem of FIG. 1.

FIG. 7 is a block diagram of an example processing system that mayexecute the example machine readable instructions of FIGS. 4, 5 and/or 6to implement the example hybrid people meters of FIGS. 2 and/or 3,and/or the example audience measurement system of FIG. 1.

DETAILED DESCRIPTION

Example methods, apparatus and articles of manufacture to implementhybrid active and passive people metering for audience measurement aredisclosed herein. As noted above, prior people meters for audiencemeasurement are generally either active or passive. An active peoplemeter obtains audience information by actively prompting an audience toenter information for audience member identification. A passive peoplemeter obtains audience information passively, usually by capturingimages of the audience using a camera and then employing facialrecognition to identify the individual audience members included in theaudience. Active people meters are generally simpler and less costlythan passive people meters, but are prone to measurement error due toaudience fatigue over time, lack of audience compliance, etc. Passivepeople meters do not rely on audience compliance and, thus, can be morereliable, but also require substantially more computing resources toimplement accurate facial recognition processing. The accuracy of thepassive people meters may also depend on their cameras being properlypositioned to capture images clearly depicting the faces of the audiencemembers. As such, passive people meters are often too costly to deployin a statistically significant number of monitored sites and/or areunable to be used in some sites to be monitored due to restrictions oncamera placement.

In contrast, people metering examples disclosed herein employ a hybridof active and passive people metering, which can improve measurementaccuracy and reduce reliance on audience compliance, but withoutincurring the costs associated with facial recognition techniques orexhibiting the camera placement restrictions associated with priorpassive people meters, in at least some examples. Example methodsdisclosed herein to perform people metering for audience measurementinclude obtaining a sequence of one or more images depicting a scene inwhich an audience is expected to be present. The example methods alsoinclude comparing an image sequence signature representative of theimage sequence with a set of reference signatures to determine acomparison result. The example methods further include controllingaudience prompting performed by a people meter based on the comparisonresult. For example, such controlling of the audience promptingperformed by the people meter can include either disabling promptingduring a current prompting interval or reducing a probability that thepeople meter will initiate an audience prompt during the currentprompting interval when the comparison result indicates that the imagesequence signature matches at least one reference signature in the setof reference signatures.

In some disclosed examples, such controlling of the audience promptingperformed by the people meter includes controlling the audienceprompting performed by the people meter based on a first configurationwhen the comparison result indicates that the image sequence signaturedoes not match at least one reference signature in the set of referencesignatures. However, the audience prompting performed by the peoplemeter is controlled based on a second configuration, which is differentfrom the first configuration, when the comparison result indicates thatthe image sequence signature matches at least one of the referencesignatures. For example, the first configuration may cause the audienceprompting performed by the people meter to occur at a first promptingfrequency. In such examples, the obtaining of the image is triggered tooccur prior to when the people meter is to initiate an audience promptduring a current prompting interval (e.g., based on the firstconfiguration). Then, if the comparison result indicates that the imagesequence signature matches at least one of the reference signatures,such example methods determine, based on the second configuration,whether to permit the audience prompt to still be initiated by thepeople meter during the current prompting interval. For example, thesecond configuration can specify that: (1) audience prompting during thecurrent prompting interval is to be disabled when the comparison resultindicates that the image sequence signature matches at least one of thereference signatures, or (2) audience prompting during the currentprompting interval is to be invoked with a probability less than onewhen the comparison result indicates that the image sequence signaturematches at least one of the reference signatures.

In some disclosed examples, the set of reference signatures can berepresentative of a respective set of prior images obtained during priorprompting intervals. Furthermore, each such reference signature can beassociated with a respective set of demographic data obtained inresponse to audience prompting performed by the people meter during theprior prompting intervals. In such examples, disclosed methods canfurther include using the demographic information associated with firstreference signature for audience identification during a currentprompting interval (e.g., instead of actively prompting the audience)when the comparison result indicates that the input image matches afirst reference signature in the set of reference signatures.

To obtain the set of reference signatures, some disclosed examplemethods include causing the people meter to initiate an audience promptduring a current prompting interval. Such example methods also includeassociating demographic information obtained in response to the audienceprompt with the image sequence signature. In such examples, the imagesequence signature is then included in the set of reference signaturesfor comparison with a second image sequence signature obtained during asubsequent prompting interval.

Example apparatus to implement hybrid active and passive people meteringfor audience measurement, and example articles of manufacture (e.g.,storage media) storing machine readable instructions which, whenexecuted, cause example machine(s) to perform hybrid active and passivepeople metering for audience measurement, are also disclosed herein.

Turning to the figures, a block diagram of an example audience meteringsystem 100 employing hybrid active and passive people metering asdisclosed herein is illustrated in FIG. 1. The example audiencemeasurement system 100 supports monitoring of media content exposure toaudiences at one or more monitored sites, such as the example monitoredsite 105 illustrated in FIG. 1. The monitored site 105 includes anexample media presentation device 110 and an example audience area 115.The audience area 115 corresponds to one or more locations at themonitored site 105 in which an audience 120 is expected to be presentwhen consuming media content (e.g., viewing and/or hearing the mediacontent, interacting with the content, etc.) presented by the mediapresentation device 110. The audience area 115 can include, but is notlimited to, a room containing the media presentation device 110, asitting area in front of the media presentation device 110, etc.Although the example of FIG. 1 illustrates one monitored site 105,hybrid active and passive people metering as disclosed herein can beused in audience measurement systems 100 supporting any number ofmonitored sites 105.

The audience measurement system 100 of the illustrated example includesan example site meter 125, also referred to as a site unit 125, a homeunit 125, etc., to monitor media content presented by the mediapresentation device 110. To support hybrid active and passive peoplemetering at the monitored site 105 in accordance with the examplesdescribed herein, the example audience measurement system 100 of FIG. 1also includes an example hybrid people meter 130, which is described ingreater detail below. In the illustrated example, the site meter 125determines audience measurement data characterizing media contentexposure at the monitored site 105 by combining metering data (alsoreferred to as content metering data, content monitoring data, contentmeasurement data, tuning data, etc.), which is determined by monitoringthe media presentation device 110, with audience identification data(also referred to as demographic data, people meter data, etc.), whichis provided by the hybrid people meter 130. The audience measurementmeter 125 then stores and reports this audience measurement data via anexample network 135 to an example data processing facility 140. The dataprocessing facility 140 performs any appropriate post-processing of theaudience measurement data to, for example, determine audience ratingsinformation, identify targeted advertising to be provided to themonitored site 105, etc. In the illustrated example, the network 130 cancorrespond to any type(s) and/or number of wired and/or wireless datanetworks, or any combination thereof.

In the illustrated example, the media presentation device 110 monitoredby the site meter 125 can correspond to any type of audio, video and/ormultimedia presentation device capable of presenting media contentaudibly and/or visually. For example, the media presentation device 110can correspond to a television and/or display device that supports theNational Television Standards Committee (NTSC) standard, the PhaseAlternating Line (PAL) standard, the Système Électronique pour Couleuravec Mémoire (SECAM) standard, a standard developed by the AdvancedTelevision Systems Committee (ATSC), such as high definition television(HDTV), a standard developed by the Digital Video Broadcasting (DVB)Project, etc. As another example, the media presentation device 110 cancorrespond to a multimedia computer system, a personal digitalassistant, a cellular/mobile smartphone, a radio, etc.

The site meter 125 included in the audience measurement system 100 ofthe illustrated example can correspond to any type of metering devicecapable of monitoring media content presented by the media presentationdevice 110. As such, the site meter 125 may utilize invasive monitoringinvolving one or more physical connections to the media presentationdevice 110, and/or non-invasive monitoring not involving any physicalconnection to the media presentation device 110. For example, the sitemeter 125 may process audio signals obtained from the media presentationdevice 110 via a microphone and/or a direct cable connection to detectcontent and/or source identifying audio codes and/or audio watermarksembedded in audio portion(s) of the media content presented by the mediapresentation device 110. Additionally or alternatively, the site meter125 may process video signals obtained from the media presentationdevice 110 via a camera and/or a direct cable connection to detectcontent and/or source identifying video codes and/or video watermarksembedded in video portion(s) of the media content presented by the mediapresentation device 110. Additionally or alternatively, the site meter125 may process the aforementioned audio signals and/or video signals togenerate respective audio and/or video signatures from the media contentpresented by the media presentation device 110, which can be compared toreference signatures to perform source and/or content identification.Any other type(s) and/or number of media content monitoring techniquescan additionally or alternatively be supported by the site meter 125.

In the example of FIG. 1, the audience measurement system 100 includesthe example hybrid people meter 130 to capture information about theaudience 120 that is consuming the media content presented by the mediapresentation device 110. A block diagram of an example implementation ofthe hybrid people meter 130 of FIG. 1 is illustrated in FIG. 2. Theexample hybrid people meter 130 of FIG. 2 includes an active peoplemeter component 205 (also referred to as the active component 205, theactive people meter 205, etc.) and an example people meter enhancementcomponent 210 (also referred to as the enhancement component 210, thepassive component 210, the people meter enhancer 210, etc.). Withreference to FIGS. 1 and 2, and as described in greater detail below,the active people meter component 205 prompts the audience 120 toactively provide audience identification information via an exampleinput interface 215. For example, the active component 205 of the hybridpeople meter 130 may cause a prompting indicator to be displayed by thehybrid people meter 130 during a current prompting interval. In suchexamples, the audience 120 can respond to the prompting indicator byusing the input interface 215 to identify which of a possible set ofaudience members are present in the audience 120.

In the illustrated example, an example prompting trigger signal 220 isprovided by the site meter 125 (not shown in FIG. 2) to control theprompting intervals during which the active people meter component 205is to prompt the audience 120 to actively provide audienceidentification information. The prompting trigger signal 220 isactivated by the site meter 125 to cause audience prompting based on,for example, a pre-configured prompting interval corresponding to apre-configured prompting frequency, a prompting interval specifiedduring configuration of the hybrid people meter 130 and corresponding toa specified prompting frequency, and/or based on monitoredcharacteristics of the media content being presented by the mediapresentation device 110 (e.g., to cause prompting to occur upondetection of events, such as channel change events, content transitionevents, audio muting/un-muting events, etc.), etc.

The example hybrid people meter 130 of FIG. 2 includes the examplepeople meter enhancement component 210 to control the audience promptingperformed by the active people meter component 205. For example, thepeople meter enhancement component 210 can reduce the frequency ofaudience prompting by passively determining audience identificationinformation for the audience 120. In some examples, the enhancementcomponent 210 of the hybrid people meter 130 includes an example imagingsensor 225, such as a camera, from which images are obtained that depicta scene in which the audience 120 is expected to be present.Accordingly, an image that is taken to be representative of audience120, such as an image taken of the audience area 115, is also referredto herein as an audience scene. For example, the imaging sensor 225 ofthe hybrid people meter 130 can be positioned such that its field ofview 230 includes the audience area 115. However, because people meterenhancement component 210 does not rely on facial recognitionprocessing, it is not necessary for the imaging sensor 225 to be placedsuch that the audience 120 is facing the imaging sensor 225, therebyremoving the camera placement restrictions associated with prior passivepeople meters. In such examples, the people meter enhancement component210 uses the captured images to attempt to recognize an audience sceneas corresponding to (e.g., matching) a past audience scene that hasalready been identified, which is referred to herein as a referenceaudience scene. If the enhancement component recognizes the audiencescene, the hybrid people meter 130 can use audience information alreadyassociated with the corresponding reference audience scene to infer orotherwise identify the audience 120. Additionally, if the audience sceneis recognized, the people meter enhancement component can block activeprompting from being performed by the hybrid people meter 130 during acurrent prompting interval, or reduce the probability of activeprompting being performed by the hybrid people meter 130 during thecurrent prompting interval (e.g., to enable verification of thereference audience's identification information).

For example, in the hybrid people meter 130 of FIG. 2, the people meterenhancement component 210 can be communicatively coupled to theprompting trigger signal 220 output by the site meter 125 and intendedfor the active people meter component 205. In such examples, the peoplemeter enhancement component 210 provides an enhanced prompting triggersignal 235 to the active people meter component 205 that is a gated orotherwise controlled version of the prompting trigger signal 220. In theillustrated example, the people meter enhancement component 210 gates(controls) the prompting trigger signal 220 by allowing the promptingtrigger signal 220 to pass to the active people meter component 205 ifthe people meter enhancement component 210 does not recognize one ormore of the audience scenes being processed, and/or is unable to inferthe audience 120 from the audience scenes. However, if the people meterenhancement component 210 does recognize the audience scenes and is ableto infer the audience 120, then the enhancement component 210 gates theprompting trigger signal 220 by blocking the prompting trigger signal220 entirely, or allowing the prompting trigger signal 220 to pass, butwith a probability less than one (which may be specified as aconfiguration parameter). Thus, by employing scene recognitionprocessing as described in greater detail below, the people meterenhancement component 210 can reduce the frequency with which theaudience 120 is actively prompted by the hybrid people meter 130.

In the illustrated example of FIG. 2, the enhancement component 210 ofthe hybrid people meter 130 reports audience identification data 240 tothe site meter 125 during the reporting intervals corresponding to theprompting trigger signal 220. In the illustrated example, when thepeople meter enhancement component is able to infer that the audience120 corresponds to (e.g., matches) a reference audience scene, theaudience identification data 240 reported by the enhancement component210 includes the reference audience identification informationassociated with the matching reference audience scene. However, when thepeople meter enhancement component 210 does not recognize the audiencescene(s) and, thus, is unable to infer the audience 120, then theaudience identification data 240 reported by the enhancement component210 includes active audience identification data 245 obtained from theactive people meter component 205 (e.g., by prompting the audience 120to actively enter the audience identification data 245 via the inputinterface 215). In some examples, when the people meter enhancementcomponent 210 infer the audience 120 from a matching reference audiencescene, the audience identification data 240 may include both thereference audience identification information and the active audienceidentification data 245 to enable verification of the reference audienceidentification information already associated with the matchingreference audience scene (e.g., such as when the enhancement component210 enables audience prompting with a probability less than one, asdescribed above).

A more detailed block diagram of the example implementation of thehybrid people meter 130 of FIG. 2 is illustrated in FIG. 3. The examplehybrid people meters 130 of FIGS. 2 and 3 include many elements incommon. As such, like elements in FIGS. 2 and 3 are labeled with thesame reference numerals. The detailed descriptions of these likeelements are provided above in connection with the discussion of FIG. 2and, in the interest of brevity, are not repeated in the discussion ofFIG. 3.

Turning to the illustrated example of FIG. 3, the active component 205of the hybrid people meter 130 includes the user interface 215 via whichaudience identification information can be obtained from the audience120. In the illustrated example, the user interface 215 includes a setof audience keys 305, such that each audience key 305 is assigned torepresent a respective possible member of the audience 120. Additionalinterface components 310, such as additional key(s), push buttons,displays, etc., are included in the user interface 215 to enablenew/guest audience members to be enrolled and associated with aparticular audience key 305 of the hybrid people meter 130. For example,the additional interface components 310 may permit a new/guest audiencemember to input demographic information, such as gender, age, etc., tothe hybrid people meter 130, after which the new/guest audience memberis associated with one of the audience keys 305. The interface 215 canalso be implemented on a remote device, which is not depicted in FIG. 3,to enable the audience 120 to interact with the active component 205remotely

In the example hybrid people meter 130 of FIG. 3, the active peoplemeter component 205 prompts the audience 120 to enter audienceidentification information via the input interface 215. For example, theactive people meter component 205 may initiate an audience prompt duringa current prompting interval by activating an example promptingindicator 315, which may correspond to a flashing light, a sound emittedby a speaker, etc. In response to perceiving the activated promptingindicator 315, the members of the audience 120 press their respectiveaudience key(s) 305 on the active people meter component 205 (and/or thecounterpart key(s) on a remote device in communication with the activepeople meter component 205) to indicate their presence in the audiencearea 115. As described above, audience prompting by the active peoplemeter component 205 is controlled by the enhanced prompting triggersignal 235 provided by the people meter enhancement component 210, andthe results of the audience prompting are reported in the activeaudience identification data 245 returned to the people meterenhancement component 210.

In the example hybrid people meter 130 of FIG. 3, the people meterenhancement component 210 includes the imaging sensor 225 (e.g., acamera) to obtain images depicting scenes in which the audience 120 isexpected to be present. As such, the people meter enhancement component210 of FIG. 3 includes an example sensor interface 320 to control theimaging sensor 225. For example, the sensor interface 320 can beimplemented using any appropriate type(s) and/or number of interface(s)to enable controlling when the imaging sensor 225 is to capture images,to enable receiving the captured images, and to enable storing thecaptured images. In the example of FIG. 3, the people meter enhancementcomponent 210 includes an example image trigger 325 to trigger when thesensor interface 320 is to cause the imaging sensor 225 to capture a newimage, or a new sequence of images, of the audience area 115. In theillustrated example, the image trigger 325 uses the prompting triggersignal 220 controlled by the site meter 125 to determine when to triggercapturing of a new image or a new sequence of images. For example, theimage trigger 325 can cause one or more images of the audience area 115to be captured each time that the prompting trigger signal 220 isactivated, thereby causing a new image sequence (containing one or morenew images) to be obtained during each prompting interval as defined bythe prompting trigger signal 220.

In some examples, the audience 120 also enters audience identificationinformation through the interface 205 of the active people metercomponent 205 without being prompted, such as when the composition ofthe audience 120 changes (e.g., due to addition of new audiencemember(s) and/or removal of existing audience member(s)). In suchexamples, the people meter enhancement component 210 may invoke theimage trigger 325 to begin capturing image(s) of the audience area 115whenever entry of audience identification information via the activepeople meter component 205 is detected, even if the prompting triggersignal 220 has not been asserted.

The people meter enhancement component 210 uses the sequence of one ormore images obtained by the imaging sensor 225 to perform audience scenerecognition, also referred to as audience inference, during a currentprompting interval. For example, the people meter enhancement component210 compares the image(s) obtained by the imaging sensor 225 during acurrent prompting interval, and which correspond to the audiencescene(s) obtained during the current prompting interval, with referenceimages representative of respective reference audience scenes that wereidentified during prior prompting intervals. If the current imagesequence matches a reference audience scene, the people meterenhancement component 210 infers that the audience 120 depicted in thecurrent image sequence corresponds to the reference audience scene. Insuch cases, the people meter enhancement component 210 can use referenceaudience identification information already associated with the matchingreference audience scene to infer the audience 120 depicted in thecurrent image sequence, and which is present in the audience area 115during the current prompting interval. Additionally, and as describedabove, the people meter enhancement component 210 can block audienceprompting or reduce the probability of audience prompting during thecurrent prompting interval when the current image sequence is determinedto match a reference audience scene.

The example people meter enhancement component 210 of FIG. 3 employsimage sequence signatures and image signature comparison to determinewhether the current image sequence obtained by the imaging sensor 225matches one or more reference scenes representative of a referenceaudience. Generally, an image sequence signature is a proxyrepresentative of the associated image sequence or a particular (e.g.,key) image from the sequence, and can take the form of, for example, oneor more digital values, a waveform, etc. In some examples, the imagesequence signature that is representative of an image sequence alsoincludes information identifying the extent of the image sequence, suchas the starting time and/or starting image frame number for thesequence, and the ending time and/or ending image frame number for thesequence. Because an image sequence signature is a proxy representingthe associated image sequence, the signatures of two image sequences canbe compared to determine whether their respective images aresubstantially similar or identical. Generally, if two image sequencesignatures match or substantially match (e.g., at least within sometolerance or deviation level), then the respective images (or imagesequences) they represent are substantially similar or identical.Typically, signature comparison is simpler and requires less processingresources than direct image comparison, and the result is more robust.

Thus, to implement image comparison for audience recognition, the peoplemeter enhancement component 210 of FIG. 3 includes an example signaturegenerator 330, an example signature comparator 335 and an examplereference storage 340. The signature generator 330 of the illustratedexample generates an image sequence signature representative of thecurrent image sequence obtained by the imaging sensor 225 during aprompting interval. In some examples, the image sequence signature(s)generated by the signature generator 330 during an observation period(e.g., a prompting interval) are each stored in a query signature, alsoreferred to as a query image signature. For example, the signaturegenerator 330 generates a respective image signature for each imageincluded in a current sequence of images obtained by the imaging sensor225 during a current prompting interval as defined by the trigger signal220. The imaging sensor 225 may generate a sequence of images, insteadof one image, during a prompting interval to account for potentialchanges in the audience composition, position, environment, etc. In suchexamples, the signature generator 330 may compare the sequence ofgenerated image signatures to identify unique signatures in thesequence, where each unique signature corresponds to a respective,unique image sequence within the overall sequence of images capturedduring the current prompting interval. These unique image sequencesignature(s), which can include information identifying the starting andending image frames and/or times defining the respective image sequencefor each unique image sequence signature, are retained and the othersignatures are discarded. The remaining, unique image sequencesignature(s), which are representative of the respective, uniquesequence(s) of images obtained by the imaging sensor 225 during acurrent prompting interval, form the query image signature for thecurrent prompting interval. As such, the query image signature isrepresentative of the overall image sequence obtained during a currentobservation (e.g., prompting interval), and can include one or more(e.g., unique) image sequence signatures representative of one or morerespective (e.g., unique) image sequences making up the overall imagesequence for the current observation interval. Further examples ofsegmenting images into unique image sequences representative of distinctaudience scenes, and using image signatures to represent such imagesequences/scenes, are discussed in U.S. application Ser. No. 13/431,626,entitled “Scene-Based People Metering for Audience Measurement,” whichwas filed on the same date as the instant application. U.S. applicationSer. No. 13/431,626, is incorporated herein by reference in itsentirety.

As described above, in some examples, the image capturing process can beperformed independently of the trigger signal 220. In such examples, theimaging sensor 225 captures a sequence of images corresponding to theaudience scenes over time. The signature generator 330 then generatesrespective image signatures for the images included in sequence,discards redundant image signatures, and uses the remaining signaturesand the query image signatures for subsequent scene recognitionprocessing.

In some examples, an image sequence signature generated by the signaturegenerator 330 corresponds to a set of image histograms of the luminanceand/or chrominance values included in the current image sequence (or akey frame representative of the current image sequence) obtained by theimaging sensor 225. Further examples of image sequence signatures thatcan be generated by the signature generator 330 include, but are notlimited to, the examples described in U.S. Patent Publication No.2011/0243459, entitled “Methods and Apparatus to Detect DifferencesBetween Images” and published on Oct. 6, 2011; U.S. Patent PublicationNo. 2009/0123025, entitled “Methods and Apparatus to Measure BrandExposure in Media Stream” and published on May 14, 2009; U.S. PatentPublication No. 2008/0068622, entitled “Methods and Apparatus toIdentify Images in Print Advertisements” and published on Mar. 20, 2008;U.S. Publication No. 2006/0153296, entitled “Digital Video SignatureApparatus and Methods for Use with Video Program Identification Systems”and published on Jul. 13, 2006; U.S. Pat. No. 6,633,651, entitled“Method and Apparatus for Recognizing Video Sequences” and issued onOct. 14, 2003; and U.S. Pat. No. 6,577,346, entitled “Recognizing aPattern in a Video Segment to Identify the Video Segment” and issued onJun. 10, 2003. U.S. Patent Publication Nos. 2011/0243459, 2009/0123025,2008/0068622 and 2006/0153296, and U.S. Pat. Nos. 6,633,651 and6,577,346, are hereby incorporated by reference in their respectiveentireties.

In the illustrated example of FIG. 3, the query image signature (orimage sequence signature(s)) generated by the signature generator 330for the current prompting interval is provided to the example signaturecomparator 335. The signature comparator 335 compares the image sequencesignature(s) included in the query image signature to one or morereference signatures stored in the reference storage 340. The referencestorage 340 may be implemented by any type of a storage or memorydevice, a database, etc., such as the mass storage device 728 and/or thevolatile memory 714 included in the example processing system 700 ofFIG. 7, which is described in greater detail below. The referencesignatures stored in the reference storage 340 are image signaturesrepresentative of respective one or more reference images, which mayalso be stored in the reference storage 340. As described above, thereference images depict respective reference audience scenes. Thesignature comparator 335 can implement any type(s) and/or number ofcomparison criteria, such as a cross-correlation value, a Hammingdistance, etc., to determine whether a query image signature and areference signature match or substantially match within a particulartolerance level (e.g., which may be predetermined, specified as aconfiguration parameter or input, etc.).

If the signature comparator 335 determines that a query image signatureand a reference signature match (e.g., corresponding to when an imagesequence signature included in the query image signature substantiallymatches a reference signature within a particular tolerance level), thenthe audience scene depicted in the current image sequence represented bythe query signature is deemed to be recognized as corresponding to thereference audience scene depicted in the reference image associated withthe matching reference signature. Thus, active audience prompting may beunnecessary. If, however, the signature comparator 335 determines thatnone of the image signatures in the query image signature match any ofthe reference signatures, then the audience scene(s) depicted in thecurrent image sequence is(are) deemed to be novel. As a result, theaudience 120 is considered to be an unknown audience for which activeaudience prompting should be performed. Accordingly, the people meterenhancement component 210 of FIG. 3 includes an example people metercontroller 345 to control audience prompting by the active people metercomponent 205 based on the result of the image sequence signaturecomparison performed by the signature comparator 335.

For example, when a comparison result determined by the signaturecomparator 335 indicates that the current query image signature for acurrent prompting interval matches at least one of the referencesignatures, the people meter controller 345 can disable audienceprompting by the active people meter component 205 during the currentprompting interval (e.g., by not asserting the enhanced promptingtrigger signal 235 during the current prompting interval).Alternatively, when the comparison result determined by the signaturecomparator 335 indicates that the query image signature matches at leastone of the reference signatures, the people meter controller 345 canreduce a probability that the active people meter component 205 willinitiate an audience prompt during the current prompting interval (e.g.,by permitting the prompting trigger signal 220 to pass through to theenhanced prompting trigger signal 235, but with a probability less thanone, such as 0.1 or some other probability value). Conversely, when thecomparison result determined by the signature comparator 335 indicatesthat the query image signature does not match any of the referencesignatures, the people meter controller 345 permits audience promptingto occur during the current prompting interval (e.g. by passing theprompting trigger signal 220 through to the enhanced prompting triggersignal 235).

In other words, the people meter controller 345 of the illustratedexample controls the audience prompting performed by the active peoplemeter component 205 based on a first configuration when the comparisonresult determined by the signature comparator 335 indicates that a queryimage signature for a current prompting interval does not match at leastone of the reference signatures. This first configuration correspondsto, for example, the original audience prompting triggered by theprompting trigger signal 220 provided by the site meter 125. However,when the comparison result determined by the signature comparator 335indicates that the query image signature matches at least one of thereference signatures, the people meter controller 345 of the illustratedexample controls the audience prompting performed by the active peoplemeter component 205 based on a second configuration, which is differentfrom the first configuration. This second configuration specifies that,for example, audience prompting during the current prompting interval isto be disabled, or that audience prompting during the current promptinginterval is to be performed with a probability less than one.

To report the audience identification data 240 during a currentprompting interval, the people meter enhancement component 210 of FIG. 3includes an example audience identifier 350. The audience identifier 350determines the audience identification data 240 to be reported based onthe result of the image sequence signature comparison performed by thesignature comparator 335. For example, when the comparison resultdetermined by the signature comparator 335 indicates that a query imagesignature matches at least one of the reference signatures, the audience120 depicted in the current image sequence has been recognized. Thus,the audience identifier 350 can use the reference audienceidentification information (e.g., reference demographic information)already associated with the matching reference signature (which isassociated with the matching reference image depicting the matchingreference audience scene) for audience identification during the currentprompting interval. In such cases, the audience identifier 350 retrievesthis reference audience identification information from the referencestorage 340 and includes it in the audience identification data 240 tobe reported during the current prompting interval.

However, when the comparison result determined by the signaturecomparator 335 indicates that the current query signature does not matchany of the reference signatures, the audience 120 depicted in thecurrent image or current sequence of images is unrecognized. Thus, theaudience identifier 350 uses the active audience identification data 245(e.g., active demographic data 245) obtained via the active people metercomponent 205 for audience identification during the current promptinginterval. In such cases, the audience identifier 350 includes the activeaudience identification data 245 in the audience identification data 240to be reported during the current prompting interval. Also, in someexamples, the audience identifier 350 associates the active audienceidentification data 245 obtained from the active people meter component205 with the current query signature and stores the current querysignature and the associated audience identification data 245 in thereference storage 340 for use as another reference audience scenesignature to be compared with a new sequence of one or more imagesobtained by imaging sensor 225 during a subsequent prompting interval

In the illustrated examples of FIGS. 2 and 3, the prompting triggersignal 220, the enhanced prompting trigger signal 235, the audienceidentification data 240 and the active audience identification data 245may be communicated using any type(s), number and/or combination(s) oftechniques, including, but not limited to, infrared (IR) transmission,radio frequency transmission, ultrasonic transmission, wired/cabledconnection, and the like.

In the preceding examples, the hybrid people meter 130 is described asbeing used in conjunction with the site meter 125. However, in someexample, the hybrid people meter 130 can operate independently of thesite meter 125, or without the site meter 125 being present in theaudience metering system 100. In such examples, the image trigger 325can cause the imaging sensor 225 to capture images of the audience scenewithout being triggered by the trigger signal 220. Each image capturedthrough sensor interface 320 is converted to an image signature by thesignature generator 330, as described above.

In some examples, the image signature generated by the signaturegenerator 330 for a currently captured image is compared with a querysignature. In such examples, the query signature corresponds to a groupof unique video signatures generated previously by the signaturegenerator 330. In some examples, the query signature is initially empty,and when a newly generated signature does not match a signature in thequery signature, the generated signature is added to the querysignature. However, when a newly generated signature matches anysignature in the query signature, the newly generated signature isdiscarded. Then, when the size of query signature exceeds a certain size(e.g., which may be preconfigured, specified, etc.), or when anobservation time period has expired (e.g., which may be preconfigured,specified, etc.), the people meter enhancement component 210 starts tomatch the image signatures included in the query signature with thereference scene signatures stored in reference storage 340.

In such examples, if the query signature does not match any of thereference scene signatures, the people meter enhancement component 210determines that novel scenes are being observed. When novel scenes areobserved, the people meter enhancement component 210 invokes the activepeople meter component 205 (e.g., via the enhanced prompting triggersignal 235) to prompt the audience 120 presented in audience area 115.Then, when the active people meter component 205 receives the audienceidentification information from the audience 120, it forwards theinformation to the people meter enhancement component 210. In someexamples, if the people meter enhancement component 210 does not receivethe audience identification information within a time window, the querysignature being processed is associated with null information, whichindicates the current scenes being processed are associated with noaudience. This information is entered into reference storage 340, withthe current audience being set to no audience. Otherwise, the querysignature being processed is associated with the audience identificationinformation obtained from the active people meter component 205, whichindicates that the current scenes being processed are associated withthis specific audience composition. This information is entered into thereference storage 340, and the current audience is identified using theinformation received from active people meter component 205.

However, when the query signature matches one or more referencesignatures from the storage 340, the people meter enhancement component210 determines that repeated audience scenes (or, in other words, arepeat of a previously processed scene) have been observed. For repeatedscenes, the current audience 120 can be identified using referenceaudience information associated with the matching reference scenesignature(s). No further help from the active meter 205 is needed. Insome examples, the people meter enhancement component 210 still requeststhe active people meter component 205 to prompt the audience 120 when,for example, the results of matching yields inconsistent audienceinformation, when the matching quality is not strong, when it isdetermined to be a time for verification based on some predeterminedprobability, etc. In some examples, when the hybrid people meter 130 isimplemented in accordance with the preceding discussion, the hybridpeople meter 130 performs audience identification processingcontinuously, and can return identification information for the currentaudience 120 whenever the site meter 125 queries for this information.

While example manners of implementing the hybrid people meter 130 ofFIG. 1 have been illustrated in FIGS. 2-3, one or more of the elements,processes and/or devices illustrated in FIGS. 2-3 may be combined,divided, re-arranged, omitted, eliminated and/or implemented in anyother way. Further, the example active people meter component 205, theexample people meter enhancement component 210, the example inputinterface 215, the example imaging sensor 225, the example sensorinterface 320, the example image trigger 325, the example signaturegenerator 330, the example signature comparator 335, the examplereference storage 340, the example people meter controller 345, theexample audience identifier 350 and/or, more generally, the examplehybrid people meter 130 of FIGS. 2-3 may be implemented by hardware,software, firmware and/or any combination of hardware, software and/orfirmware. Thus, for example, any of the example active people metercomponent 205, the example people meter enhancement component 210, theexample input interface 215, the example imaging sensor 225, the examplesensor interface 320, the example image trigger 325, the examplesignature generator 330, the example signature comparator 335, theexample reference storage 340, the example people meter controller 345,the example audience identifier 350 and/or, more generally, the examplehybrid people meter 130 could be implemented by one or more circuit(s),programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)), etc. When any of the apparatusor system claims of this patent are read to cover a purely softwareand/or firmware implementation, at least one of the example hybridpeople meter 130, the example active people meter component 205, theexample people meter enhancement component 210, the example inputinterface 215, the example imaging sensor 225, the example sensorinterface 320, the example image trigger 325, the example signaturegenerator 330, the example signature comparator 335, the examplereference storage 340, the example people meter controller 345 and/orthe example audience identifier 350 are hereby expressly defined toinclude a tangible computer readable medium such as a memory, digitalversatile disk (DVD), compact disk (CD), Blu-ray disc™, etc., storingsuch software and/or firmware. Further still, the example hybrid peoplemeter 130 of FIGS. 2-3 may include one or more elements, processesand/or devices in addition to, or instead of, those illustrated in FIG.2-3, and/or may include more than one of any or all of the illustratedelements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the example hybrid people meter 130, the example activepeople meter component 205, the example people meter enhancementcomponent 210, the example input interface 215, the example imagingsensor 225, the example sensor interface 320, the example image trigger325, the example signature generator 330, the example signaturecomparator 335, the example reference storage 340, the example peoplemeter controller 345 and/or the example audience identifier 350 areshown in FIGS. 4-6. In these examples, the machine readable instructionsrepresented by each flowchart may comprise one or more programs forexecution by a processor, such as the processor 712 shown in the exampleprocessing system 700 discussed below in connection with FIG. 7. The oneor more programs, or portion(s) thereof, may be embodied in softwarestored on a tangible computer readable medium such as a CD-ROM, a floppydisk, a hard drive, a digital versatile disk (DVD), a Blu-ray disc™, ora memory associated with the processor 712, but the entire program orprograms and/or portions thereof could alternatively be executed by adevice other than the processor 712 (e.g., such as a controller and/orany other suitable device) and/or embodied in firmware or dedicatedhardware (e.g., implemented by an ASIC, a PLD, an FPLD, discrete logic,etc.). Also, one or more of the machine readable instructionsrepresented by the flowchart of FIGS. 4-6 may be implemented manually.Further, although the example machine readable instructions aredescribed with reference to the flowcharts illustrated in FIGS. 4-6,many other methods of implementing the example hybrid people meter 130,the example active people meter component 205, the example people meterenhancement component 210, the example input interface 215, the exampleimaging sensor 225, the example sensor interface 320, the example imagetrigger 325, the example signature generator 330, the example signaturecomparator 335, the example reference storage 340, the example peoplemeter controller 345 and/or the example audience identifier 350 mayalternatively be used. For example, with reference to the flowchartsillustrated in FIGS. 4-6, the order of execution of the blocks may bechanged, and/or some of the blocks described may be changed, eliminated,combined and/or subdivided into multiple blocks.

As mentioned above, the example processes of FIGS. 4-6 may beimplemented using coded instructions (e.g., computer readableinstructions) stored on a tangible computer readable medium such as ahard disk drive, a flash memory, a read-only memory (ROM), a CD, a DVD,a cache, a random-access memory (RAM) and/or any other storage media inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, brief instances, for temporarily buffering, and/orfor caching of the information). As used herein, the term tangiblecomputer readable medium is expressly defined to include any type ofcomputer readable storage and to exclude propagating signals.Additionally or alternatively, the example processes of FIGS. 4-6 may beimplemented using coded instructions (e.g., computer readableinstructions) stored on a non-transitory computer readable medium, suchas a flash memory, a ROM, a CD, a DVD, a cache, a random-access memory(RAM) and/or any other storage media in which information is stored forany duration (e.g., for extended time periods, permanently, briefinstances, for temporarily buffering, and/or for caching of theinformation). As used herein, the term non-transitory computer readablemedium is expressly defined to include any type of computer readablemedium and to exclude propagating signals. Also, as used herein, theterms “computer readable” and “machine readable” are consideredequivalent unless indicated otherwise. Furthermore, as used herein, whenthe phrase “at least” is used as the transition term in a preamble of aclaim, it is open-ended in the same manner as the term “comprising” isopen ended. Thus, a claim using “at least” as the transition term in itspreamble may include elements in addition to those expressly recited inthe claim.

Example machine readable instructions 400 that may be executed toimplement the example hybrid people meter 130 of FIGS. 1, 2 and/or 3 arerepresented by the flowchart shown in FIG. 4. The example machinereadable instructions 400 may be executed at predetermined intervals,based on an occurrence of a predetermined event, etc., or anycombination thereof. For convenience and without loss of generality, theexample machine readable instructions 400 are described in the contextof execution by the hybrid people meter 130 of FIG. 3 in the audiencemeasurement system 100 of FIG. 1. With reference to the precedingfigures, the machine readable instructions 400 of FIG. 4 begin executionat block 405 at which the image trigger 325 of the enhancement component210 of the hybrid people meter 130 receives an asserted promptingtrigger signal 220 from the site meter 125 of the audience measurementsystem 100, which indicates the start of the current audience promptinginterval, as described above. At block 410, the image trigger 325triggers the sensor interface 320 of the people meter enhancementcomponent 210 to cause its imaging sensor 225 to obtain a sequence ofone or more images of the audience area 115 for the current promptinginterval. As described above, the image(s) obtained at block 410 depictscene(s) in which an audience (e.g., the audience 120) is expected to bepresent. At block 415, the signature generator 330 of the people meterenhancement component 210 generates query image signature(s)representative of the image(s) obtained at block 410, as describedabove.

At block 420, the signature comparator 335 of the people meterenhancement component 210 compares the query image signature(s)generated at block 415 with a set of reference signatures retrieved fromthe reference storage 340 to determine a comparison result. As describedabove, the reference signatures are representative of reference imagesdepicting reference audience scenes previously identified by the hybridpeople meter 130. Thus, the comparison result determined at block 420indicates whether the audience 120 depicted in the current imagesequence can be inferred from the previous known/reference scenes or isto be determined using the active component 205. At block 425, thepeople meter controller 345 controls audience prompting performed by theactive component 205 of the hybrid people meter 130 by, for example,generating the enhanced prompting trigger signal 235 based on thecomparison result determined by the signature comparator 335 at block420. For example, and as described above, the people meter controller345 may permit audience prompting to occur according to the promptingtrigger signal 220 when the comparison result indicates that theaudience 120 depicted in the current image sequence cannot be inferredbecause the image sequence is novel, whereas when the comparison resultindicates that the audience 120 depicted in the current image sequencecan be inferred from the previous (e.g., reference) image sequences, thepeople meter controller 345 may block audience prompting or permitaudience prompting to still occur (e.g., to verify the referenceaudience identification information associated with the matchingreference audience). Processing then returns to block 405 and blockssubsequent thereto to enable audience recognition and identification tobe performed during a subsequent prompting interval.

Second example machine readable instructions 500 that may be executed toimplement the example hybrid people meter 130 of FIGS. 1, 2 and/or 3 arerepresented by the flowchart shown in FIG. 5. The example machinereadable instructions 500 may be executed at predetermined intervals,based on an occurrence of a predetermined event, etc., or anycombination thereof. For convenience and without loss of generality, theexample machine readable instructions 500 are described in the contextof execution by the hybrid people meter 130 of FIG. 3 in the audiencemeasurement system 100 of FIG. 1. Also, FIG. 5 includes blocks 405-420from FIG. 4. Accordingly, the processing performed by the examplemachine readable instructions 500 at these blocks is described in detailabove in connection with the discussion of FIG. 4 and, in the interestof brevity, is not repeated in the discussion of FIG. 5.

With reference to the preceding figures, the machine readableinstructions 500 of FIG. 5 begin execution at block 405 and perform theprocessing at blocks 405 through 420 as described above in connectionwith the description of the machine readable instructions 400 of FIG. 4.Thus, after completion of the processing at block 420, the signaturecomparator 335 of the enhancement component 210 of the hybrid peoplemeter 130 has determined a result of comparing the query image signaturerepresentative of the current image sequence (e.g., depicting theaudience 120) with the set of reference signatures, which arerepresentative of the set of reference images depicting the set ofreference audiences previously identified by the hybrid people meter130. Next, at block 505 the signature comparator 335 determines whetherthe query image signature representative of the current image sequencematches at least one of the reference signatures (e.g., corresponding toat least one of the image sequence signatures in the query imagesignature matching at least one of the reference signatures). If a queryimage signature matches a reference signature (block 505), then at block510 the people meter controller 345 of the people meter enhancementcomponent 210 disables audience prompting by the active people metercomponent 205 during the current prompting interval. For example, thepeople meter controller 345 can disable audience prompting by blockingthe prompting trigger signal 220 received from the site meter 125 frombeing passed through to the enhanced prompting trigger signal 235provided to the active people meter component 205, as described above.

At block 515, the audience identifier 350 of the people meterenhancement component 210 retrieves, from the reference storage 340, thereference audience identification information (e.g., referencedemographic information) that has been associated with the matchingreference signature. At block 515, the audience identifier 350 inheritsor otherwise uses the reference audience identification information toinfer the audience 120 depicted in the image sequence for the currentprompting interval, as described above. At block 520, the audienceidentifier 350 reports the audience identification data 240 for thecurrent prompting interval, which includes the reference audienceidentification information that has been associated with the audience120 depicted in the current image sequence, as described above.

However, if the query image signature does not match any of thereference signatures (block 505), then at block 525 the people metercontroller 345 permits audience prompting by the active people metercomponent 205 during the current prompting interval. For example, thepeople meter controller 345 can enable audience prompting by passing theprompting trigger signal 220 received from the site meter 125 through tothe enhanced prompting trigger signal 235 provided to the active peoplemeter component 205, as described above. At block 530, the audienceidentifier 350 receives the active audience identification data 245(e.g., demographic data 245) generated by the active people metercomponent 205 during the current prompting interval. As described above,the active audience identification data 245 is obtained from theaudience 120 via the input interface 215 in response to an audienceprompt triggered by the active people meter component 205. At block 535,the audience identifier 350 associates the active audienceidentification data 245 with the query signature of the current imagesequence. At block 535, the audience identifier 350 also stores thecurrent query signature and audience identification in the referencestorage 340 to be used as reference information for comparison with anew image sequence obtained during a subsequent prompting interval. Atblock 540, the audience identifier 350 reports the audienceidentification data 240 for the current prompting interval, whichincludes the active audience identification data 245 that has beenassociated with the audience 120 depicted in the current image, asdescribed above. Processing then returns to block 405 and blockssubsequent thereto to enable audience recognition and identification tobe performed during a subsequent prompting interval.

Third example machine readable instructions 600 that may be executed toimplement the example hybrid people meter 130 of FIGS. 1, 2 and/or 3 arerepresented by the flowchart shown in FIG. 6. The example machinereadable instructions 600 may be executed at predetermined intervals,based on an occurrence of a predetermined event, etc., or anycombination thereof. For convenience and without loss of generality, theexample machine readable instructions 600 are described in the contextof execution by the hybrid people meter 130 of FIG. 3 in the audiencemeasurement system 100 of FIG. 1. Also, FIG. 6 includes blocks 405-420from FIG. 4, and blocks 505 and 515-540 from FIG. 5. Accordingly, theprocessing performed by the example machine readable instructions 600 atthese blocks is described in detail above in connection with thediscussions of FIGS. 4-5 and, in the interest of brevity, is notrepeated in the discussion of FIG. 6.

With reference to the preceding figures, the machine readableinstructions 600 of FIG. 6 begin execution at block 405 and perform theprocessing at blocks 405 through 420 as described above in connectionwith the description of the machine readable instructions 400 of FIG. 4.Thus, after completion of the processing at block 420, the signaturecomparator 335 of the enhancement component 210 of the hybrid peoplemeter 130 has determined a result of comparing the query image signaturerepresentative of the current image sequence (e.g., depicting theaudience 120) with the set of reference signatures, which arerepresentative of the set of reference images depicting the set ofreference audiences previously identified by the hybrid people meter130. Next, at block 505 the signature comparator 335 determines whetherthe query image signature representative of the current image sequencematches at least one of the reference signatures. If the query imagesignature does not match any of the reference signatures (block 505),then the processing at blocks 525 through 540 is performed. As describedabove in connection with the description of the machine readableinstructions 400 of FIG. 4, the processing at blocks 525 through 540causes the audience 120 depicted in the current image to be identifiedvia active audience prompting performed by the active component 205 ofthe hybrid people meter 130.

However, if current query image signature does match at least one of thereference signatures (block 505), then at block 605 the people metercontroller 345 of the people meter enhancement component 210 reduces theprobability that the active people meter component 205 will initiate anaudience prompt during the current prompting interval. For example, andas described above, the people meter controller 345 can reduce theprobability of audience prompting during the current prompting intervalby permitting the prompting trigger signal 220 to pass through to theenhanced prompting trigger signal 235, but gated with a probability lessthan one. In some examples, the people meter controller 345 can use arandom number generator to gate whether the prompting trigger signal 220is passed through to the enhanced prompting trigger signal 235 with thespecified or configured probability. If audience prompting ends up beingblocked by the people meter controller 345 during the current promptinginterval (block 610), then the processing at blocks 515 and 520 isperformed. As described above in connection with the description of themachine readable instructions 400 of FIG. 4, the processing at blocks515 and 520 causes the audience 120 depicted in the current image to beidentified using the reference audience identification informationalready associated with the reference signature that matched the currentimage sequence signature. However, if audience prompting ends up beingpermitted by the people meter controller 345 during the currentprompting interval (block 610), then the processing at blocks 525through 540 is performed to enable the audience 120 depicted in thecurrent image to be identified via active audience prompting performedby the active component 205 of the hybrid people meter 130, as describedabove. Processing then returns to block 405 and blocks subsequentthereto to enable audience recognition and identification to beperformed during a subsequent prompting interval.

FIG. 7 is a block diagram of an example processing system 700 capable ofexecuting the instructions of FIGS. 4-6 to implement the example hybridpeople meter 130, the example active people meter component 205, theexample people meter enhancement component 210, the example inputinterface 215, the example imaging sensor 225, the example sensorinterface 320, the example image trigger 325, the example signaturegenerator 330, the example signature comparator 335, the examplereference storage 340, the example people meter controller 345 and/orthe example audience identifier 350 of FIGS. 1-3. The processing system700 can be, for example, a server, a personal computer, a mobile phone(e.g., a smartphone, a cell phone, etc.), a personal digital assistant(PDA), an Internet appliance, a DVD player, a CD player, a digital videorecorder, a Blu-ray player, a gaming console, a personal video recorder,a set top box, a digital camera, or any other type of computing device.

The system 700 of the instant example includes a processor 712. Forexample, the processor 712 can be implemented by one or moremicroprocessors and/or controllers from any desired family ormanufacturer.

The processor 712 includes a local memory 713 (e.g., a cache) and is incommunication with a main memory including a volatile memory 714 and anon-volatile memory 716 via a bus 718. The volatile memory 714 may beimplemented by Static Random Access Memory (SRAM), Synchronous DynamicRandom Access Memory (SDRAM), Dynamic Random Access Memory (DRAM),RAMBUS Dynamic Random Access Memory (RDRAM) and/or any other type ofrandom access memory device. The non-volatile memory 716 may beimplemented by flash memory and/or any other desired type of memorydevice. Access to the main memory 714, 716 is controlled by a memorycontroller.

The processing system 700 also includes an interface circuit 720. Theinterface circuit 720 may be implemented by any type of interfacestandard, such as an Ethernet interface, a universal serial bus (USB),and/or a PCI express interface.

One or more input devices 722 are connected to the interface circuit720. The input device(s) 722 permit a user to enter data and commandsinto the processor 712. The input device(s) can be implemented by, forexample, a keyboard, a mouse, a touchscreen, a track-pad, a trackball, atrackbar (such as an isopoint), a voice recognition system and/or anyother human-machine interface.

One or more output devices 724 are also connected to the interfacecircuit 720. The output devices 724 can be implemented, for example, bydisplay devices (e.g., a liquid crystal display, a cathode ray tubedisplay (CRT)), a printer and/or speakers. The interface circuit 720,thus, typically includes a graphics driver card.

The interface circuit 720 also includes a communication device, such asa modem or network interface card, to facilitate exchange of data withexternal computers via a network 726 (e.g., an Ethernet connection, adigital subscriber line (DSL), a telephone line, coaxial cable, acellular telephone system, etc.).

The processing system 700 also includes one or more mass storage devices728 for storing machine readable instructions and data. Examples of suchmass storage devices 728 include floppy disk drives, hard drive disks,compact disk drives and digital versatile disk (DVD) drives. In someexamples, the mass storage device 728 may implement the referencestorage 340. Additionally or alternatively, in some examples thevolatile memory 714 may implement the reference storage 340.

Coded instructions 732 corresponding to the instructions of FIGS. 4-6may be stored in the mass storage device 728, in the volatile memory714, in the non-volatile memory 716, in the local memory 713 and/or on aremovable storage medium, such as a CD or DVD 736.

As an alternative to implementing the methods and/or apparatus describedherein in a system such as the processing system of FIG. 7, the methodsand or apparatus described herein may be embedded in a structure such asa processor and/or an ASIC (application specific integrated circuit).

Finally, although certain example methods, apparatus and articles ofmanufacture have been described herein, the scope of coverage of thispatent is not limited thereto. On the contrary, this patent covers allmethods, apparatus and articles of manufacture fairly falling within thescope of the appended claims either literally or under the doctrine ofequivalents.

What is claimed is:
 1. A method to perform people metering for audiencemeasurement, the method comprising: obtaining an image sequence, whichdepicts a scene in which an audience is expected to be present, prior towhen a people meter is to initiate an audience prompt; and gatingtransmission of a trigger signal to the people meter based on a resultof comparing an image sequence signature representative of the imagesequence with a set of reference signatures, the trigger signal totrigger performance of audience prompting by the people meter.
 2. Amethod as defined in claim 1, wherein gate transmission of the triggersignal to the people meter includes disabling transmission of thetrigger signal to the people meter during a first prompting intervalwhen the result indicates that the image sequence signature matches atleast one reference signature in the set of reference signatures.
 3. Amethod as defined in claim 1, wherein gating transmission of the triggersignal to the people meter includes reducing a probability oftransmitting the trigger signal to the people meter during a firstprompting interval when the result indicates that the image sequencesignature matches at least one reference signature in the set ofreference signatures.
 4. A method as defined in claim 1, wherein gatingtransmission of the trigger signal to the people meter includes: gatingtransmission of the trigger signal to the people meter based on a firstconfiguration when the result indicates that the image sequencesignature does not match at least one reference signature in the set ofreference signatures; and gating transmission of the trigger signal tothe people meter based on a second configuration when the resultindicates that the image sequence signature matches at least one of thereference signatures, the second configuration being different from thefirst configuration.
 5. A method to perform people metering for audiencemeasurement, the method comprising: obtaining an image sequencedepicting a scene in which an audience is expected to be present;comparing an image sequence signature representative of the imagesequence with a set of reference signatures to determine a comparisonresult; controlling audience prompting performed by a people meter basedon a first configuration when the comparison result indicates that theimage sequence signature does not match at least one reference signaturein the set of reference signatures; triggering the obtaining of theimage sequence to occur prior to when the people meter is to initiate anaudience prompt during a current prompting interval based on the firstconfiguration, the first configuration to cause the audience promptingperformed by the people meter to occur at a first prompting frequency;controlling the audience prompting performed by the people meter basedon a second configuration when the comparison result indicates that theimage sequence signature matches at least one of the referencesignatures, the second configuration being different from the firstconfiguration; and when the comparison result indicates that the imagesequence signature matches at least one of the reference signatures,determining, based on the second configuration, whether to permit theaudience prompt to be initiated by the people meter during the currentprompting interval, the second configuration specifying that at leastone of: (1) audience prompting during the current prompting interval isto be disabled when the comparison result indicates that the imagesequence signature matches at least one of the reference signatures, or(2) audience prompting during the current prompting interval is to beinvoked with a probability less than one when the comparison resultindicates that the image sequence signature matches at least one of thereference signatures.
 6. A method as defined in claim 1, wherein the setof reference signatures are representative of a respective set of priorimages obtained during prior prompting intervals, each referencesignature is associated with a respective set of demographic dataobtained in response to audience prompting by the people meter duringthe prior prompting intervals, and the method further includes, when theresult indicates that the image sequence signature matches a firstreference signature in the set of reference signatures, using thedemographic information associated with the first reference signaturefor audience identification during a first prompting interval.
 7. Amethod as defined in claim 1, further including: causing the peoplemeter to initiate the audience prompt during a first prompting interval;associating demographic information obtained in response to the audienceprompt with the image sequence signature; and including the imagesequence signature in the set of reference signatures for comparisonwith a second image sequence signature obtained during a subsequentprompting interval.
 8. A tangible machine readable storage mediumcomprising machine readable instructions which, when executed, cause amachine to at least: obtain of an image sequence, which depicts a scenein which an audience is expected to be present, prior to when a peoplemeter is to initiate an audience prompt; and gate transmission of atrigger signal to the people meter based on a result of comparing animage sequence signature representative of the image sequence with a setof reference signatures, the trigger signal to trigger performance ofaudience prompting by the people meter.
 9. A storage medium as definedin claim 8, wherein to gate transmission of the trigger signal to thepeople meter, the machine readable instructions, when executed, furthercause the machine to disable transmission of the trigger signal to thepeople meter during a first prompting interval when the result indicatesthat the image sequence signature matches at least one referencesignature in the set of reference signatures.
 10. A storage medium asdefined in claim 8, wherein to gate transmission of the trigger signalto the people meter, the machine readable instructions, when executed,further cause the machine to reduce a probability of transmitting thetrigger signal to the people meter during a first prompting intervalwhen the result indicates that the image sequence signature matches atleast one reference signature in the set of reference signatures.
 11. Astorage medium as defined in claim 8, wherein to gate transmission ofthe trigger signal to the people meter, the machine readableinstructions, when executed, further cause the machine to: gatetransmission of the trigger signal to the people meter based on a firstconfiguration when the result indicates that the image sequencesignature does not match at least one reference signature in the set ofreference signatures; and gate transmission of the trigger signal to thepeople meter based on a second configuration when the result indicatesthat the image sequence signature matches at least one of the referencesignatures, the second configuration being different from the firstconfiguration.
 12. A tangible machine readable storage medium comprisingmachine readable instructions which, when executed, cause a machine toat least: compare an image sequence signature representative of an imagesequence in which an audience is expected to be present with a set ofreference signatures to determine a comparison result; control audienceprompting performed by a people meter based on a first configurationwhen the comparison result indicates that the image sequence signaturedoes not match at least one reference signature in the set of referencesignatures; trigger obtaining of the image sequence to occur prior towhen the people meter is to initiate an audience prompt during a currentprompting interval based on the first configuration, the firstconfiguration to cause the audience prompting performed by the peoplemeter to occur at a first prompting frequency; control the audienceprompting performed by the people meter based on a second configurationwhen the comparison result indicates that the image sequence signaturematches at least one of the reference signatures, the secondconfiguration being different from the first configuration; and when thecomparison result indicates that the image sequence signature matches atleast one of the reference signatures, determine, based on the secondconfiguration, whether to permit the audience prompt to be initiated bythe people meter during the current prompting interval, the secondconfiguration specifying that at least one of: (1) audience promptingduring the current prompting interval is to be disabled when thecomparison result indicates that the image sequence signature matches atleast one of the reference signatures, or (2) audience prompting duringthe current prompting interval is to be invoked with a probability lessthan one when the comparison result indicates that the image sequencesignature matches at least one of the reference signatures.
 13. Astorage medium as defined in claim 8, wherein the set of referencesignatures are representative of a respective set of prior imagesobtained during prior prompting intervals, each reference signature isassociated with a respective set of demographic data obtained inresponse to audience prompting by the people meter during the priorprompting intervals, and the machine readable instructions, whenexecuted, further cause the machine to, when the result indicates thatthe image sequence signature matches a first reference signature in theset of reference signatures, use the demographic information associatedwith the first reference signature for audience identification during afirst prompting interval.
 14. A storage medium as defined in claim 8,wherein the machine readable instructions, when executed, further causethe machine to: cause the people meter to initiate the audience promptduring a first prompting interval; associate demographic informationobtained in response to the audience prompt with the image sequencesignature; and include the image sequence signature in the set ofreference signatures for comparison with a second image sequencesignature obtained during a subsequent prompting interval.
 15. Anapparatus to perform people metering for audience measurement, theapparatus comprising: a people meter to obtain audience identificationinformation; and an enhancer to: obtain an image sequence, which depictsa scene in which an audience is expected to be present, prior to when apeople meter is to initiate an audience prompt; and gate transmission ofa trigger signal to the people meter based on a result of comparing animage sequence signature representative of the image sequence with a setof reference signatures, the trigger signal to trigger performance ofaudience prompting by the people meter.
 16. An apparatus as defined inclaim 15, wherein the enhancer is to disable transmission of the triggersignal to the people meter during a first prompting interval when theresult indicates that the image sequence signature matches at least onereference signature in the set of reference signatures.
 17. An apparatusas defined in claim 15, wherein the enhancer is to reduce a probabilityof transmitting the trigger signal to the people meter during a firstprompting interval when the result indicates that the image sequencesignature matches at least one reference signature in the set ofreference signatures.
 18. An apparatus as defined in claim 15, whereinthe enhancer is to: gate transmission of the trigger signal to thepeople meter based on a first configuration when the result indicatesthat the image sequence signature does not match at least one referencesignature in the set of reference signatures; and gate transmission ofthe trigger signal to the people meter based on a second configurationwhen the result indicates that the image sequence signature matches atleast one of the reference signatures, the second configuration beingdifferent from the first configuration.
 19. An apparatus to performpeople metering for audience measurement, the apparatus comprising: apeople meter to obtain audience identification information; an enhancerto: obtain an image sequence depicting a scene in which an audience isexpected to be present; compare an image sequence signaturerepresentative of the image sequence with a set of reference signaturesto determine a comparison result; control audience prompting performedby the people meter based on a first configuration when the comparisonresult indicates that the image sequence signature does not match atleast one reference signature in the set of reference signatures; and animage trigger to cause the image sequence to be obtained prior to whenthe people meter is to initiate an audience prompt during a currentprompting interval based on the first configuration, the firstconfiguration to cause the audience prompting performed by the peoplemeter to occur at a first prompting frequency; and when the comparisonresult indicates that the image sequence signature matches at least oneof the reference signatures, the enhancer is to determine, based on asecond configuration different from the first configuration, whether topermit the audience prompt to be initiated by the people meter duringthe current prompting interval, the second configuration specifying thatat least one of: (1) audience prompting during the current promptinginterval is to be disabled when the comparison result indicates that theimage sequence signature matches at least one of the referencesignatures, or (2) audience prompting during the current promptinginterval is to be invoked with a probability less than one when thecomparison result indicates that the image sequence signature matches atleast one of the reference signatures.
 20. An apparatus to performpeople metering for audience measurement, the apparatus comprising: apeople meter to obtain audience identification information; and anenhancer to: obtain an image sequence depicting a scene in which anaudience is expected to be present; compare an image sequence signaturerepresentative of the image sequence with a set of reference signaturesto determine a comparison result; and control audience promptingperformed by the people meter based on the comparison result; whereinthe set of reference signatures are representative of a respective setof prior images obtained during prior prompting intervals, eachreference signature is associated with a respective set of demographicdata obtained in response to audience prompting by the people meterduring the prior prompting intervals, and the apparatus furtherincludes: an audience identifier to: use first demographic informationassociated with a first reference signature in the set of referencesignatures for audience identification during a current promptinginterval when the comparison result indicates that the image sequencesignature matches the first reference signature; and associate seconddemographic information obtained via the people meter during the currentprompting interval with the image sequence signature when the comparisonresult indicates that the image sequence signature does not match atleast one reference signature in the set of reference signatures; and amemory to store the image sequence signature in the set of referencesignatures for comparison with a second image sequence signatureobtained during a subsequent prompting interval.